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语义单元:将知识图组织成具有语义意义的表示单元。

Semantic units: organizing knowledge graphs into semantically meaningful units of representation.

机构信息

TIB Leibniz Information Centre for Science and Technology, Welfengarten 1B, 30167, Hanover, Germany.

Department of Computer Science, Vrije Universiteit, Amsterdam, Netherlands.

出版信息

J Biomed Semantics. 2024 May 27;15(1):7. doi: 10.1186/s13326-024-00310-5.

Abstract

BACKGROUND

In today's landscape of data management, the importance of knowledge graphs and ontologies is escalating as critical mechanisms aligned with the FAIR Guiding Principles-ensuring data and metadata are Findable, Accessible, Interoperable, and Reusable. We discuss three challenges that may hinder the effective exploitation of the full potential of FAIR knowledge graphs.

RESULTS

We introduce "semantic units" as a conceptual solution, although currently exemplified only in a limited prototype. Semantic units structure a knowledge graph into identifiable and semantically meaningful subgraphs by adding another layer of triples on top of the conventional data layer. Semantic units and their subgraphs are represented by their own resource that instantiates a corresponding semantic unit class. We distinguish statement and compound units as basic categories of semantic units. A statement unit is the smallest, independent proposition that is semantically meaningful for a human reader. Depending on the relation of its underlying proposition, it consists of one or more triples. Organizing a knowledge graph into statement units results in a partition of the graph, with each triple belonging to exactly one statement unit. A compound unit, on the other hand, is a semantically meaningful collection of statement and compound units that form larger subgraphs. Some semantic units organize the graph into different levels of representational granularity, others orthogonally into different types of granularity trees or different frames of reference, structuring and organizing the knowledge graph into partially overlapping, partially enclosed subgraphs, each of which can be referenced by its own resource.

CONCLUSIONS

Semantic units, applicable in RDF/OWL and labeled property graphs, offer support for making statements about statements and facilitate graph-alignment, subgraph-matching, knowledge graph profiling, and for management of access restrictions to sensitive data. Additionally, we argue that organizing the graph into semantic units promotes the differentiation of ontological and discursive information, and that it also supports the differentiation of multiple frames of reference within the graph.

摘要

背景

在当今的数据管理领域,知识图谱和本体的重要性日益凸显,因为它们是与 FAIR 指导原则相一致的关键机制,确保数据和元数据是可查找、可访问、可互操作和可重复使用的。我们讨论了可能阻碍充分发挥 FAIR 知识图谱潜力的三个挑战。

结果

我们引入了“语义单元”作为一种概念性解决方案,尽管目前仅在一个有限的原型中得到例证。语义单元通过在传统数据层之上添加另一层三元组,将知识图谱结构化为可识别和具有语义意义的子图。语义单元及其子图由它们自己的资源表示,该资源实例化相应的语义单元类。我们将语句单元和复合单元区分作为语义单元的基本类别。语句单元是对于人类读者具有语义意义的最小、独立的命题。根据其基础命题的关系,它由一个或多个三元组组成。将知识图谱组织成语句单元会导致图形的分区,每个三元组恰好属于一个语句单元。另一方面,复合单元是语句和复合单元的语义上有意义的集合,形成更大的子图。一些语义单元将图形组织成不同层次的表示粒度,其他语义单元则以不同类型的粒度树或不同的参考框架正交地组织图形,将知识图形结构化为部分重叠、部分封闭的子图,每个子图都可以通过自己的资源引用。

结论

语义单元可应用于 RDF/OWL 和标记属性图,为语句和图形对齐、子图匹配、知识图形分析以及对敏感数据的访问限制提供支持。此外,我们认为将图形组织成语义单元可以促进本体论和论述信息的区分,并且还支持图形内多个参考框架的区分。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/8555/11131308/4b37e633b19b/13326_2024_310_Fig1_HTML.jpg

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